Crystal Transformer: Self-learning neural language model for Generative and Tinkering Design of Materials

no code implementations • 25 Apr 2022 • Lai Wei, Qinyang Li, Yuqi Song, Stanislav Stefanov, Edirisuriya M. D. Siriwardane, Fanglin Chen, Jianjun Hu

Here we propose BLMM Crystal Transformer, a neural network based probabilistic generative model for generative and tinkering design of inorganic materials.

Language Modelling Self-Learning +1

MaterialsAtlas.org: A Materials Informatics Web App Platform for Materials Discovery and Survey of State-of-the-Art

no code implementations • 9 Sep 2021 • Jianjun Hu, Stanislav Stefanov, Yuqi Song, Sadman Sadeed Omee, Steph-Yves Louis, Edirisuriya M. D. Siriwardane, Yong Zhao

The availability and easy access of large scale experimental and computational materials data have enabled the emergence of accelerated development of algorithms and models for materials property prediction, structure prediction, and generative design of materials.

Band Gap Materials Screening +1